Stochastic error rate estimation for adaptive speed control with field delay testing

This paper proposes a stochastic framework for error rate estimation that models adaptive speed control as a continuous-time Markov process and derives its transition rates using developed similarity database. The proposed framework is implemented for adaptive speed control systems based on timing error prediction and scan-test. Experimental results show that the proposed framework enabled 12 orders of magnitude faster MTTF estimation than ordinary logic simulation. The accuracy of MTTF estimation under random delay fluctuation is clarified through a comparison with logic simulation. The proposed estimation can contribute to design and validation of adaptive speed control systems with field delay testing.